Kaplan-Meier Product-Limit Method
Creates Kaplan-Meier product limit estimator. Specifying survival times: There are three ways to specify survival times. You can select one (continuous dependent) variable with survival times (e.g., number of weeks surviving), you can select two (continuous dependent) variables with start and stop times for each observation (the analysis will be performed on the differences between the two values, i.e., on the elapsed times), or you can select six (continuous dependent) variables containing dates. Specifically, these variables should contain the month (1 to 12), day (1 to 31), and year when the particular observation began (e.g., when the patient was admitted to the hospital), and the month, day, and year when the observation was terminated (due to death/failure or censoring, e.g., when a patient was dismissed from the hospital). While processing the data, Survival Analysis will compute the number of days that elapsed between dates, and perform the analysis on this measure. Note that if the value of the year is less than 100, Statistica will automatically assume that the year refers to the 20th century; for example, the year 88 would be converted into 1988 (and 3 would be converted to 1903; make sure to enter 2003 explicitly into the year column to reference that year).
General
| Element Name | Description |
|---|---|
| Percentiles | Creates and reports estimates of the 25th, 50th, and 75th percentile of the survival function. Note that Statistica will interpolate values if the respective quartile boundary is not exactly defined by an uncensored case. |
| Survival Function | Creates and reports a plot of survival times vs. cumulative proportion surviving. |
| Log-survival | Creates and reports a plot of the log (survival times) vs. cumulative proportion surviving. |
| Log-log Plot | Creates and reports a plot of log (survival times) vs. log (cumulative proportion surviving). |